Does observance of Ramadan affect sleep in athletes and physically active individuals? A systematic review and meta‐analysis
Bibliographic record
Abstract
The purpose of this systematic review and meta-analysis is to provide an accurate description of the effect of Ramadan observance on sleep duration, sleep quality, daily nap duration, and daytime sleepiness in athletes and physically active individuals. Five electronic databases (PubMed, Web of Science, Scopus, Wiley, and Taylor and Francis) were used to search for relevant studies conducted with athletes or physically active individuals during Ramadan, published in any language, and available before May 23, 2021. Studies that included assessments of sleep quantity and/or quality, and/or daytime sleepiness, and/or daily naps in athletes and physically active individuals were included. The methodological quality of the studies was assessed using "QualSyst". Of the 18 papers included in this study (298 participants in total), 14 were of strong quality, two were moderate, and the remaining two were rated as weak. Individuals who continued to train during Ramadan experienced a decrease in sleep duration (number of studies, K = 17, number of participants, N = 289, g = -0.766, 95% confidence interval [CI] -1.199 to -0.333, p = 0.001). Additionally, the global score of the Pittsburgh Sleep Quality Index increased from 4.053 (K = 5, N = 65, 95% CI 3.071-5.034) pre-Ramadan, to 5.346 (95% CI 4.362-6.333) during Ramadan, indicating a decrease in sleep quality. The duration of daytime naps increased during compared to pre-Ramadan (K = 2, N = 31, g = 1.020, 95% CI 0.595-1.445, p = 0.000), whereas Epworth Sleepiness Scale scores remained unchanged during versus pre-Ramadan (K = 3, N = 31, g = 0.190, 95% CI -0.139-0.519, p = 0.257). In conclusion, individuals who continued to train during Ramadan experienced a decrease in sleep duration, impairment of sleep quality, and increase in daytime nap duration, with no change in daytime sleepiness levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".